suppressPackageStartupMessages({
library(tidyverse)
library(tidyr)
library(here)
library(ggplot2)
library(dplyr)
library(readxl)
library(devtools)
library(plotly)
library(base)
library(rio)
library(plyr)
})
Note: Corbett’s ITQ data is only until 2012. Chris’s upside data is now updated until 2016 with the more recent RAM data that Dan had. I ran all the figure and regressions under two “scenerios”:
1. until 2012
2. past 2012. extracted information about which fisheries had ITQs in 2012 and applied it to the same fisheries into the future. This doesn't take into account other fisheries that get ITQs in place during that time, or if fisheries stop ITQs
“KOBE” plots with ITQs not updated past 2012
ITQ_projection <- readRDS("data/ITQ_projection.rds")
f_b_itq <- ITQ_projection %>%
select("BvBmsy", "FvFmsy", "itq", "iq", "ivq", "turf", "Catch") %>%
filter( itq != "NA", iq != "NA", ivq != "NA") %>%
mutate(rightsbased = case_when(
itq == TRUE | iq == TRUE | ivq == TRUE ~ "1",
itq == FALSE & iq == FALSE & ivq == FALSE ~ "0"))
F_B_graph <- ggplot(data = f_b_itq, aes( x=BvBmsy, y=FvFmsy, colour= rightsbased, size = Catch ))+
geom_point()+
labs(x = "B/Bmsy", y= "F/Fsmy") +
theme_minimal()+
theme(legend.title=element_blank())+
ylim(-1, 5)+
xlim(-.3, 3)+
geom_hline(aes(yintercept=1))+
geom_vline(aes(xintercept=1))
#F_B_graph
ggplotly(F_B_graph)
“KOBE” plots with ITQs updated past 2012
ITQ_projection_updated <- readRDS("data/ITQ_projection_updated.rds")
f_b_itq_updated <- ITQ_projection_updated %>%
select("BvBmsy", "FvFmsy", "itq", "iq", "ivq", "turf", "Catch") %>%
filter( itq != "NA", iq != "NA", ivq != "NA") %>%
mutate(rightsbased = case_when(
itq == TRUE | iq == TRUE | ivq == TRUE ~ "1",
itq == FALSE & iq == FALSE & ivq == FALSE ~ "0"))
F_B_graph_updated <- ggplot(data = f_b_itq_updated, aes( x=BvBmsy, y=FvFmsy, colour= rightsbased, size = Catch ))+
geom_point()+
labs(x = "B/Bmsy", y= "F/Fsmy") +
theme_minimal()+
theme(legend.title=element_blank())+
ylim(-1, 5)+
xlim(-.3, 3)+
geom_hline(aes(yintercept=1))+
geom_vline(aes(xintercept=1))
#F_B_graph
ggplotly(F_B_graph_updated)